Adaptive fuzzy relational predictive control

被引：9

作者：

Wong, CH ^{[1
]}

Shah, SL ^{[1
]}

Bourke, MM ^{[1
]}

Fisher, DG ^{[1
]}

机构：

[1] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2G6, Canada

来源：

FUZZY SETS AND SYSTEMS | 2000年 / 115卷 / 02期

关键词：

process control; fuzzy identification; fuzzy control; adaptive control; long-range prediction; fuzzy relational structures;

D O I：

10.1016/S0165-0114(98)00295-4

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The performance of Two fuzzy relational controllers namely the self-learning predictive fuzzy controller (SLPFC) (Bourke and Fisher, Proc. 5th Int. Conf. on Fuzzy Systems, New Orleans, 1996, pp. 464-1470) and the fuzzy relational long range predictive controller (FRLRPC) (Postlethwaite, IEE Proc. D 138(3) (1991) 199-206) are evaluated experimentally on a laboratory scale, non-linear, interacting tank process. Both fuzzy controllers gave good closed-loop control performance but the SLPFC gave slightly better results. It was also found that the choice of the on-line fuzzy relational identification scheme has a large impact on control performance. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

引用

页码：247 / 260

页数：14

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